PSY 207 Lecture Notes - Lecture 7: Central Limit Theorem, Sampling Distribution, Standard Deviation
Document Summary
Ch 7: probability and sampling: the sampling distribution of sample means. Inferential statistics: we now know how to use the standard normal curve to determine probabilities associated with specific raw scores (x). Makes use of probabilities to test hypotheses about populations based on samples. Could be samples with size of n = 1. But, we"ll almost never use sample sizes of n = 1. Better yet, a sample composed of multiple raw scores (i. e. n > 1) In this case, we would be determining the probability of obtaining a particular sample mean (m) Problem: we will almost never actually know the actual mean and standard deviation of a population. If we knew the actual mean and standard deviation, we wouldn"t need to draw a sample: we need tools for computing probabilities of larger samples ( n > 1) Even when we don"t know the mean ( ) and standard deviation ( ) of the population.
